Assessing Splanchnic Compartment Using Portal Venous Doppler and Impact of Adding It to the EVEREST Score for Risk Assessment in Heart Failure
Bibliographic record
Abstract
Background The Efficacy of Vasopressin Antagonism in Heart Failure: Outcome Study with Tolvaptan (EVEREST) score has proven useful for risk prediction in acute decompensated heart failure (ADHF). However, this score does not include the characterization of the splanchnic compartment, which has been involved in worsening heart failure. Refining this score by integrating an assessment of the splanchnic compartment would allow for a better risk assessment. Therefore, we aimed to characterize the patterns of portal vein pulsatility (PVP), an ultrasound metric used for the assessment of splanchnic compartment and their determinants in patients with ADHF, to explore the relationships between abnormal patterns of PVP and outcomes, and to evaluate the added value of PVP to the EVEREST score for risk assessment in ADHF. Methods Portal vein flow was assessed prospectively on admission and at discharge in 95 patients with ADHF using pulsed-wave Doppler. Abnormal PVP was defined for values ≥ 50%. Cox proportional hazards models were used for the assessment of the relationship between PVP and outcomes. Results Overall, 64% of patients on admission and 24% at discharge had abnormal PVP. PVP on admission was inversely correlated with right ventricular function (tricuspid annular plane systolic excursion, ρ = −0.434) and pulmonary pressure (ρ = 0.346), P < 0.05. Although PVP was associated with all-cause mortality (hazard ratio, 1.028, P < 0.001), the addition of this metric to the EVEREST score had little effect on its C-index (0.813 vs 0.818) for risk assessment. Conclusions Abnormal PVP is frequent and associated with right ventricular dysfunction in ADHF. Although abnormal PVP identifies higher-risk patients, this metric does not improve the performance of the EVEREST score for risk assessment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".